samsung SM-S938W
Geekbench AI Score
522
Single Precision Score
515
Half Precision Score
1095
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Mystline |
| Upload Date | February 01 2025 02:49 AM |
| Views | 17 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938W |
| Model ID | samsung SM-S938W |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
422
78.5 IPS |
|
|
Image Classification (HP)
|
100% |
419
78.0 IPS |
|
|
Image Classification (Q)
|
99% |
1057
197.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
539
8.74 IPS |
|
|
Image Segmentation (HP)
|
100% |
496
8.04 IPS |
|
|
Image Segmentation (Q)
|
98% |
966
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
674
0.79 IPS |
|
|
Pose Estimation (HP)
|
100% |
647
0.75 IPS |
|
|
Pose Estimation (Q)
|
98% |
1942
2.27 IPS |
|
|
Object Detection (SP)
|
100% |
334
26.5 IPS |
|
|
Object Detection (HP)
|
100% |
335
26.6 IPS |
|
|
Object Detection (Q)
|
87% |
881
70.7 IPS |
|
|
Face Detection (SP)
|
100% |
639
7.60 IPS |
|
|
Face Detection (HP)
|
100% |
636
7.55 IPS |
|
|
Face Detection (Q)
|
97% |
1562
18.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
584
4.50 IPS |
|
|
Depth Estimation (HP)
|
99% |
606
4.67 IPS |
|
|
Depth Estimation (Q)
|
64% |
1451
13.2 IPS |
|
|
Style Transfer (SP)
|
100% |
1163
1.49 IPS |
|
|
Style Transfer (HP)
|
100% |
1010
1.30 IPS |
|
|
Style Transfer (Q)
|
98% |
2621
3.38 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
258
9.53 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
283
10.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1017
37.7 IPS |
|
|
Text Classification (SP)
|
100% |
367
489.6 IPS |
|
|
Text Classification (HP)
|
100% |
367
489.4 IPS |
|
|
Text Classification (Q)
|
91% |
616
827.5 IPS |
|
|
Machine Translation (SP)
|
100% |
718
12.4 IPS |
|
|
Machine Translation (HP)
|
100% |
731
12.6 IPS |
|
|
Machine Translation (Q)
|
57% |
384
9.40 IPS |
